US 12,467,692 B2Granted

Flame analytics system

AssigneeHoneywell International Inc.

InventorsDavid Kucera, Curtis Taylor, Jonathan McDonald, Gregory Stewart, Wyatt Culler

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Abstract

A flame analytics system that may incorporate a burner, one or more sensors at the burner, a historical database connected to the one or more sensors, a model training module connected to the historical database, and a runtime algorithm module connected to the one or more sensors and the model training module. The runtime algorithm may compare realtime data from the one or more sensors and historical data from the model training module in accordance with a machine learning algorithm. The system may further incorporate a fault detection module connected to the runtime algorithm module, a fault diagnostics module connected to the fault detection module, and an enunciator connected to the fault detection module. The one or more sensors may also include having video or acoustic sensitivity of combustion in the burner.

Claims18

Dependent claims

A flame analytics system, comprising:

a burner;
one or more sensors at or about the burner, wherein the one or more sensors include two or more video sensors positioned at different angles with respect to a flame in the burner, and wherein the two or more video sensors are configured to capture video data pertaining to the flame, wherein the video data comprise 2D views of the flame;
a processor configured to:
reconstruct the 2D views of the flame into 3D views of the flame, wherein the 3D views of the flame are utilized to distinguish the flame from a background of the flame in the video data, and
determine one or more parameters associated with the flame based on the 3D views of the flame;
a historical database connected to the one or more sensors;
a model training module connected to the historical database, wherein a machine learning algorithm is trained based on the historical database;
and
a runtime algorithm module connected to the one or more sensors and the model training module, wherein the runtime algorithm module compares real time data from the one or more sensors and the historical data from the model training module in accordance with the machine learning algorithm.

6 more elements

A method, for detecting a burner fault, comprising:

obtaining runtime data of a burner from combustion sensors associated with the burner;
processing the runtime data by a machine learning mechanism, wherein the machine learning mechanism receives historical data of the burner from a database, and the runtime data, wherein the machine learning mechanism comprises a machine learning model, the machine learning model comprises an air side submodel;
a fuel side submodel, and a combustion submodel, wherein the combustion submodel further incorporates video data provided by one or more video sensors of a combustion process of the burner, wherein the video data are post-processed before being sent to the machine learning model, wherein an image of the post-processed video is automatically segmented in that the image is binarized using a combination of pixel values in each color channel, and a resulting binary image being divided into adjacent geometric regions, wherein a statistical measure between the pixel values in each color channel is created for each segment of the image, and wherein statistical measures are input to the combustion submodel of the machine learning model;
and
comparing the historical data and the runtime data of the burner to detect the burner fault.

2 more elements

Dependencies are inferred from the claim text.

Facts

Application: 18/397,833Filed 27 Dec 2023 · continuation
Priority: 2 Nov 2018
Published: US 2024/0125554 A118 Apr 2024
Granted: 11 Nov 2025
Term ends: Not estimatedThe source records don’t support an estimate.

Classification24 codes

F27D 21/04
Arrangement of monitoring devices; Arrangement of safety devices: arrangement of indicators or alarms
F23N 5/082
Using light-sensitive elements: using electronic means
F23N 5/16
Systems for controlling combustion: using noise-sensitive detectors
F23N 5/242
Preventing development of abnormal or undesired conditions, i.e. safety arrangements: using electronic means

Family

Application62/755,297Us provisional application · filed 2 Nov 2018
Application16/665,572Parent of this continuation · filed 28 Oct 2019
US 2024/0125554 A1Pre-grant publication · published 18 Apr 2024
US 11,898,800 B2Parent of this continuation
US 2020/0141653 A1Published application
US 12,467,692 B2This patent

From the US filing history. Foreign family members aren’t listed.